Women Politicians Responding to Patriarchy in Postconflict Nepal
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Women’s movements have played a crucial role in fighting for women’s rights and freedoms. Some women join the armed movements in search of equality. Women have participated in grassroots movements demanding space in the political arena. For example, postwar countries like Burundi, Nepal, Sri Lanka and Rwanda have effectively passed women’s quota seats (as part of a peace deal) thanks to women’s movements, and this has helped women to enter politics. Despite the formal progress in descriptive representation, women politicians face backlash. Feminist scholars argue that the rise of anti-feminist values threatens women’s gains. Building on this argument, this study investigates how female politicians responded to patriarchy in postwar Nepal. It asks how women who enter political spaces navigate patriarchy while sustaining their political positions and power. The paper's findings offer three distinct categories of female politicians (risk-takers, opportunity seekers, and opt-to-disengage). Categorization unpacks diverse strategies and tactics women politicians developed to respond to patriarchy, retain positions and power, and make their current and future political and personal decisions. The study relies on thirty-one in-depth interviews conducted with women politicians. This paper enhances existing debates on patriarchy and women politicians and an understanding of quota politics.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it